author       = "Yelensky, Roman and Bonakdar, Sasha and Wolfish, Cara S.
                      and Cotsapas, Chris and Rivas, Manuel and Dermitzakis,
                      Emmanouil T. and Choy, Edwin and Plenge, Robert M. and
                      Saxena, Richa and De Jager, Philip Lawrence and Shaw,
                      Stanley Yang and Slavik, Jacqueline Marie and
                      Cahir-McFarland, Ellen D. and Kieff, Elliott D. and Hafler,
                      David A. and Daly, Mark Joseph and Altshuler, David Matthew",
      title        = "Genetic Analysis of Human Traits In Vitro: Drug Response
                      and Gene Expression in Lymphoblastoid Cell Lines",
      month        = "Oct",
      year         = "2010",
      note         = "Lymphoblastoid cell lines (LCLs), originally collected as
                      renewable sources of DNA, are now being used as a model
                      system to study genotype–phenotype relationships in human
                      cells, including searches for QTLs influencing levels of
                      individual mRNAs and responses to drugs and radiation. In
                      the course of attempting to map genes for drug response
                      using 269 LCLs from the International HapMap Project, we
                      evaluated the extent to which biological noise and
                      non-genetic confounders contribute to trait variability in
                      LCLs. While drug responses could be technically well
                      measured on a given day, we observed significant day-to-day
                      variability and substantial correlation to non-genetic
                      confounders, such as baseline growth rates and metabolic
                      state in culture. After correcting for these confounders, we
                      were unable to detect any QTLs with genome-wide significance
                      for drug response. A much higher proportion of variance in
                      mRNA levels may be attributed to non-genetic factors
                      (intra-individual variance—i.e., biological noise, levels
                      of the EBV virus used to transform the cells, ATP levels)
                      than to detectable eQTLs. Finally, in an attempt to improve
                      power, we focused analysis on those genes that had both
                      detectable eQTLs and correlation to drug response; we were
                      unable to detect evidence that eQTL SNPs are convincingly
                      associated with drug response in the model. While LCLs are a
                      promising model for pharmacogenetic experiments, biological
                      noise and in vitro artifacts may reduce power and have the
                      potential to create spurious association due to